KHAEMENES ACADEMY · CHEMISTRY 11 · WEEK 17 · DAY 04

Virtual Solution-Stoichiometry Investigation

Use supplied titration-style data to infer an unknown amount without exposing students to reactive chemicals.

Safety boundary

Use oxidation-number analysis, supplied datasets, and approved simulations. Any solution work should remain virtual or teacher-supervised with classroom-safe materials.

Explicit chemistry instruction

This investigation uses supplied or simulated volume/concentration data only.

Preserve raw trial volumes before averaging. Convert each trial to moles using the known concentration, then apply the reaction ratio.

Compare repeated trials and identify an outlier only with documented evidence, not because it is inconvenient.

Vocabulary: titration concept; trial; equivalence; unknown concentration; repeatability.

Worked example

A 20.00 mL unknown reacts 1:1 with 0.1000 M standard. If equivalence occurs at 18.40 mL standard, moles standard=0.001840 mol, so the unknown contains the same moles.

Guided question

Which raw measurements are necessary to infer an unknown concentration in a 1:1 simulated titration?

Independent work

  1. Preserve all trial volumes.
  2. Calculate standard moles for each trial.
  3. Infer unknown concentration.
  4. Report spread, uncertainty, and one revision.

Investigation / Data Lab

Use supplied or simulated data only. Preserve raw trials, calculations, stoichiometric reasoning, uncertainty, and one revision.

Misconception check

A single perfect-looking trial is weaker evidence than repeatable trials with documented spread.

Formative check

What makes repeated solution-stoichiometry trials stronger evidence?

Reveal response

They reveal repeatability and help distinguish random variation from a single anomalous result.

Mentor evidence conference

Ask Archaemenes to audit oxidation-number changes, mole accounting, equivalence assumptions, and uncertainty.

Teacher guidance

Foundation: Use supplied trial tables.

Core: Complete full unknown-concentration inference.

Extended: Assess an outlier with quantitative justification.